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Brief Summary of Book: Data Science and Machine Learning Applications in Subsurface Engineering by Daniel Asante Otchere
Provided below is a brief overview along with the book cover of “Data Science and Machine Learning Applications in Subsurface Engineering” authored by Daniel Asante Otchere, officially released on February 6, 2024. Prior to downloading the complete PDF of the book, you may peruse this information located at the bottom.
This comprehensive volume delves into various aspects of machine learning (ML) as applied to subsurface engineering, encompassing unsupervised learning, supervised learning, clustering techniques, feature engineering, and explainable AI, along with multioutput regression models.
Emphasizing the handling of vast and intricate datasets, the field of ML focuses on developing data-driven methodologies and computational algorithms capable of discerning complex, non-linear patterns. The objective is to comprehend and forecast relationships between variables through in-depth data analysis.
While ML models ultimately yield predictions, this book underscores the importance of several preliminary steps to ensure accuracy, including data pre-processing, feature selection, feature engineering, and outlier removal. It goes beyond conventional ML models by introducing novel models built upon existing architecture and learning theories, enhancing performance and adaptability to both small and large datasets without necessitating manual adjustments.
This research-oriented work serves as a valuable resource for subsurface engineers, geophysicists, and geoscientists, providing insights into the latest advancements in data science and ML relevant to subsurface engineering.
Furthermore, it illustrates the application of data-driven methodologies in diverse areas such as salt identification, seismic interpretation, enhanced oil recovery factor estimation, pore fluid type prediction, petrophysical property forecasting, pipeline pressure drop estimation, bubble point pressure prediction, drilling mud loss mitigation, smart well completion, and synthetic well log predictions.
Data Science and Machine Learning Applications in Subsurface Engineering by Daniel Asante Otchere – eBook Details
Before embarking on the download of “Data Science and Machine Learning Applications in Subsurface Engineering” in PDF by Daniel Asante Otchere, it is prudent to acquaint yourself with the technical details of this ebook:
- Full Book Name: Data Science and Machine Learning Applications in Subsurface Engineering
- Author: Daniel Asante Otchere
- Genre: Non-Fiction, Tech Devices
- Series: Not specified
- ISBN: 9781032433646
- ASIN: 1032433647
- Edition Language: English
- Date of Publication: February 6, 2024
- PDF File Name: Data_Science_and_Machine_Learning_-_Daniel_Asante_Otchere.pdf
- PDF File Size: 28 MB
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